The present invention relates to a method for defining a boundary between a solid object model and a fluid model for computational fluid dynamics simulations, more particularly to a high speed algorithm for separating a coordinate system mesh into a fluid region and a solid region.
In recent years, computational fluid dynamics simulations are utilized in various fields in order to analyze various flow types such as: flow of air around a golf ball, flow of rubber out of an extruder, and flow of composite materials in a mixing device for the purpose of developing the dimples capable of improving flying characteristics of the golf ball, the extruder having a reduced resistance to extrusion, and the mixing device capable of improving the property of the composite for example.
In the computational fluid dynamics simulations, usually, grid points are arranged in a region of three-dimensional space in a basic coordinate system, and
a fluid model is defined by the grid points at which physical quantities such as temperature, pressure, velocity and the like of the fluid are defined.
On the other hand, a solid object model is defined by finite elements having node points.
For example in case of immersed boundary method or Chimera method, where the solid object model overlaps with the grid points which are arranged in the three-dimensional space to define the fluid model, it is necessary to know which of the grid points are positioned inside the solid object model, and which of the grid points are positioned outside the solid object model, and it is very important to quickly define the boundary between the fluid region and solid region on the grid points.
In order to define the boundary on the grid points, the most commonly employed method is such that, for each of the node points positioned at the surface of the solid object model, the grid points are searched for a point nearest to the node point under consideration.
This type of search is known as Nearest neighbor search.
The approaches to accelerate Nearest neighbor search heretofore proposed can be classified into two types:
1) narrowing candidates of nearest neighbors, and
2) pruning of distance computation.
In such accelerated Nearest Neighbor search, however, when the number of the grid points and node points is increased, the computing time becomes still long.
Even in the recently developed Nearest neighbor search algorithms such as ANN and kd-Tree, the same type of problems arise.
Therefore, in such fluid dynamics simulations that the solid object model is moved and/or deformed, the search and definition of boundary points have to be made iteratively, therefore, hitherto known inefficient slow Nearest Neighbor search algorithms involve enormous computing time.